scmap
A tool for unsupervised projection of single cell RNA-seq data
Bioconductor version: 3.24 · Package version: 1.35.0
Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment on to the cell-types or individual cells identified in a different experiment.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scmap") Details
| Maintainer | Vladimir Kiselev <vladimir.yu.kiselev@gmail.com> |
| Author | Vladimir Kiselev |
| License | GPL-3 |
| URL | https://github.com/hemberg-lab/scmap |
| Bug Reports | https://support.bioconductor.org/t/scmap/ |
| Downloads rank | 915 |
| Source branch | devel |
| biocViews | Classification, DataImport, DataRepresentation, GeneExpression, ImmunoOncology, Preprocessing, RNASeq, Sequencing, SingleCell, Software, SupportVectorMachine, Transcription, Transcriptomics, Visualization |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | scmap_1.35.0.tar.gz |
| Windows binary (x86_64) | scmap_1.35.0.zip |
| macOS binary (arm64) | scmap_1.35.0.tgz |
| macOS binary (x86_64) | scmap_1.35.0.tgz |
Dependencies
Depends: R (>= 3.4)
Imports: Biobase, SingleCellExperiment, SummarizedExperiment, BiocGenerics, S4Vectors, dplyr, reshape2, matrixStats, proxy, utils, googleVis, ggplot2, methods, stats, e1071, randomForest, Rcpp (>= 0.12.12)
LinkingTo: Rcpp, RcppArmadillo